


from collections.abc import Callable

import numpy as np






def 					UpperCamelCase   (      __magic_name__	:				Callable       ,       __magic_name__	:				float       ,       __magic_name__	:				float       ,       __magic_name__	:				float       ,       __magic_name__	:				float	)  ->    np.array:
		"""simple docstring"""




		lowercase__	     =						int(np.ceil((x_end - xa) / step_size	)	)
		lowercase__	     =						np.zeros((n + 1,)	)
		lowercase__	     =						ya
		lowercase__	     =						xa

		for k in range(__magic_name__	):
				lowercase__	     =						y[k] + step_size * ode_func(__magic_name__       ,       y[k]	)
				lowercase__	     =						y[k] + (
				    (step_size / 2) * (ode_func(__magic_name__       ,       y[k]	) + ode_func(x + step_size       ,       __magic_name__	))
				)
				x += step_size

		return y


if __name__ == "__main__":
	import doctest

	doctest.testmod()








'''simple docstring'''






import fire

from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer






def   __A    (				a_    :	str   ,a_    :	str   ,**a_    :	int						):
		lowerCAmelCase  :     str       						= AutoConfig.from_pretrained(a_   ,**a_						)
		lowerCAmelCase  :     Any       						= AutoModelForSeqaSeqLM.from_config(a_						)
		model.save_pretrained(a_						)
		AutoTokenizer.from_pretrained(a_						).save_pretrained(a_						)
		return model


if __name__ == "__main__":
					fire.Fire(save_randomly_initialized_version)



